This means there are two important decisions to make before we train a artificial neural network: (i) the overall architecture of the system (how input nodes represent given examples, how many hidden ...

The number of hidden layers gives rise to the concept of deep learning ... In the case of supervised ANNs, researchers train the neural network by feeding in data with known values or features.

Artificial neural networks have been applied to problems ... This is usually done by adding an extra (hidden) layer of threshold units each of which does a partial classification of the input ...

An example of TEECNet model structure with 3 hidden layers and hidden layer dimension of 32. Credit: Journal of Computational ...